An unbiased approach of molecular characterization of the endometrium: toward defining endometrial-based infertility

Infertility is a complex condition affecting millions of couples worldwide. The current definition of infertility, based on clinical criteria, fails to account for the molecular and cellular changes that may occur during the development of infertility. Recent advancements in sequencing technology and single-cell analysis offer new opportunities to gain a deeper understanding of these changes. The endometrium has a potential role in infertility and has been extensively studied to identify gene expression profiles associated with (impaired) endometrial receptivity. However, limited overlap among studies hampers the identification of relevant downstream pathways that could play a role in the development of endometrial-related infertility. To address these challenges, we propose sequencing the endometrial transcriptome of healthy and infertile women at the single-cell level to consistently identify molecular signatures. Establishing consensus on physiological patterns in endometrial samples can aid in identifying deviations in infertile patients. A similar strategy has been used with great success in cancer research. However, large collaborative initiatives, international uniform protocols of sample collection and processing are crucial to ensure reliability and reproducibility. Overall, the proposed approach holds promise for an objective and accurate classification of endometrial-based infertility and has the potential to improve diagnosis and treatment outcomes.

Automated summary

Infertility is a complex condition with molecular and cellular changes that need to be studied further. Recent advancements in sequencing technology and single-cell analysis offer opportunities to better understand these changes. The endometrium may play a role in infertility, but the lack of consistency among studies hampers the identification of relevant pathways. By sequencing the endometrial transcriptome at the single-cell level, molecular signatures can be consistently identified, aiding in the identification of deviations in infertile patients.